VesselVio is an open-source application designed for the analysis and visualization of segmented vasculature datasets.

There are several ways to use VesselVio:

• Download the app for Windows and MacOS.
• Run the app from your terminal by using the VesselVio.py file (single-line executable)
  • Follow the Windows & MacOS build instructions here
• Modify the analysis pipeline and add custom analyses using the VVTerminal.py file

VesselVio is compatible with several different types of segmented vasculature datasets, including:

• Segmented vascular volumes from any imaging source (e.g., LSFM, µCT)
• Annotated volumes, including:
  • Whole-brain vasculature datasets with Allen Brain Institute ID-based annotations
  • Manually labelled datasets with a program such as ITK-Snap
  • RGB-based annotations, such as those created with QuickNII
• Pre-constructed graphs (both edge- and vertex- based graphs)
• 2D and 3D datasets
• Isotropic and Anisotropic datasets

VesselVio reconstructs vascular networks to extract whole-network and individual segment features. Several examples of feature outputs can be seen below.

Visualization with VesselVio is made possible with PyVista, an intuitive and high-level VTK package. Thanks to PyVista, users can easily visualize and examine their vasculature datasets with numerous options to create for accompanying figure images.

If you are looking for help with segmenting your vasculature, there are numerous packages available for this process¹²³.

Contributions to VesselVio are absolutely welcome! The guide to contributing should be read and followed. Briefly, Issues should be used for bug reports and feature requests. Discussions and Slack should be used for general support or tutorial requests. Pull-requests should follow the guidelines described in the contributing document. Thank you!

Any suggestions, improvements, or comments should be directed to Jacob Bumgarner.

Feel free to join us on Slack for general communication or troubleshooting purposes!

If you use VesselVio in your research, please cite our publication in Cell Reports Methods.

Bumgarner JR, and Nelson RJ. (2022). Open-source analysis and visualization of segmented vasculature datasets with VesselVio. Cell Rep Methods 2, 100189. https://doi.org/10.1016/j.crmeth.2022.100189

BibTex:

@article{bumgarner2022vesselvio,
title = {Open-source analysis and visualization of segmented vasculature datasets with VesselVio},
journal = {Cell Reports Methods},
volume = {2},
number = {4},
pages = {100189},
year = {2022},
issn = {2667-2375},
doi = {https://doi.org/10.1016/j.crmeth.2022.100189},
url = {https://www.sciencedirect.com/science/article/pii/S2667237522000443},
author = {Jacob R. Bumgarner and Randy J. Nelson},
}